218results about How to "Avoid restrictions" patented technology

The invention discloses a wind power equipment coating corrosion state monitoring method and device, equipment, a storage medium and a program product, and relates to the technical field of wind power generation, and the wind power equipment coating corrosion state monitoring method comprises the steps: obtaining equipment parameters of offshore wind power equipment and environment parameters collected by a sensor on the offshore wind power equipment; based on the equipment parameters and the environment parameters, establishing a digital twinborn model corresponding to the offshore wind power equipment; according to the digital twinborn model, the change condition of the coating state of the offshore wind power equipment is simulated, predicted coating state parameters are output, and the predicted coating state parameters at least comprise the coating corrosion state and the coating thickness of the offshore wind power equipment at the current time point. The technical problems that an existing wind power equipment coating corrosion state monitoring scheme is greatly limited by the environment, the workload is high, and the detection cost is high are solved.

The invention belongs to the technical field of computer vision, and particularly relates to a medical image classification method based on priori knowledge enhanced masks and alignment modeling. Comprising the following steps: acquiring an image text pair data set and preprocessing the image text pair data set to obtain a preprocessed image text pair data set; performing preliminary training on a visual encoder and a text encoder according to the preprocessed image text pair data set to obtain a preliminarily trained visual encoder and a preliminarily trained text encoder; training the visual encoder for the second time in combination with the text encoder to obtain a trained visual encoder; classifying the medical images by adopting the trained visual encoder; the model provided by the invention can be better generalized to various downstream medical image recognition tasks, and the accuracy of the downstream medical image recognition tasks is improved.

The invention discloses a micro-kernel Hypervisor-based virtual machine cross-operating system communication method, which comprises the following steps of: creating virtual machines which independently run in respective operating system environments by a micro-kernel Hypervisor, then constructing a shared memory between two virtual machines with communication requirements, respectively initializing virtual machine shared equipment by the two virtual machines, and storing the virtual machine shared equipment in the shared memory; according to the cross-operating-system communication method, the shared memory is mapped to a virtual address of the shared memory, when one virtual machine needs to transmit data to the opposite side, communication is initiated to write the data into the shared memory, and the virtual machine receiving the data reads the data from the shared memory, so that cross-operating-system communication of the virtual machines is realized. Based on the shared memory technology, the communication process of the shared memory and the virtual machines is managed by using the microkernel Hypervisor, and cross-operating system communication between the virtual machines is realized.

The invention discloses an intelligent reservoir scheduling method based on a near-end strategy optimization algorithm, and relates to the technical field of reservoir application. According to the method, a reservoir is modeled into an intelligent agent, the intelligent agent is composed of two neural networks of the same structure and interacts with a scheduling environment, network parameters are updated by adopting a near-end strategy optimization (PPO) algorithm, simulated reservoir inflow and forecast flow data are generated through an ARMA model according to historical actually-measured runoff data, and the intelligent agent is trained; the real-time scheduling performance of the intelligent agent is verified by using historical actually measured runoff data, behavior actions are expressed in a probability distribution form, the limitation of dimensionality disaster of a traditional algorithm is effectively avoided, and the Agent can more flexibly adjust a scheduling strategy by observing the water level and the incoming water condition in real time, so that the decision process is closer to an actual scheduling scene.

The invention relates to the technical field of target detection, in particular to a target detection method, device and equipment based on multi-sensor fusion and a storage medium, and the method comprises the steps: tracking a target in real time through a millimeter wave radar, a photosensitive sensor and an infrared sensor, and judging the state of the target. According to the invention, the method can achieve the recognition of environment interference through the fusion of the three types of sensor data, has more intelligent environment adaptability, has excellent adaptability in different weathers and different scenes, can obtain more comprehensive target information through the mutual complementation of the three types of sensor data, and improves the detection accuracy and reliability.

The invention discloses an Internet of Things HTTP fuzzing method based on a large language model, and relates to the technical field of Internet of Things HTTP fuzzing. The method comprises the following steps: data acquisition: adopting a data acquisition strategy to obtain data for the HTTP fuzzy test of the Internet of Things; data preprocessing: preprocessing the collected data, and providing high-quality input data for subsequent fuzzy testing; hTTP structure sensing guided by LLM: using a prompt adjustment method to label fuzzy variables in request data by using the LLM, understanding a protocol data structure, and guiding a variation process; lLM-guided seed template expansion: expanding a seed bank by enriching data packets and expanding field values; lLM-guided seed variation and seed scheduling: optimizing test results by intelligently selecting and managing input seeds. According to the method, the efficiency and accuracy of fuzzy testing can be improved, and the vulnerability detection capability is enhanced.

The invention discloses a flow field numerical simulation method for autonomous swimming of underwater bionic fish, and particularly relates to the field of bionic fish swimming flow field numerical simulation, which comprises the step of describing the shape of a fish body by establishing a contour line equation of a horizontal section. The global ground coordinate system and the fish body coordinate system are associated through the gravity center position and the pitch angle of the fish body, and a time sequence fish body motion data set is established. And generating a time sequence flow field data set by combining unsteady flow field data acquired by the distributed underwater sensor array. And based on the flow field control equation and the dynamic motion characteristics of the fish body, constructing a static interactive coupling model, extracting key dynamic characteristic quantities, and establishing a flow field prediction model. And inputting interactive coupling data to the static model to calculate a global coupling solution for error analysis, and generating a dynamic interactive coupling model. And according to the flow field prediction result and the dynamic interactive coupling model, correcting the motion characteristic data of the fish body, optimizing the motion trail of the bionic fish, and realizing closed-loop optimization of the flow field and the fish body motion.

The present invention provides an indirect prediction method for milling force based on power signal considering tool wear. By establishing a theoretical power consumption model and considering the influence of tool wear on cutting force, the influence relationship from tool wear to cutting force and then to machine tool power is established from the mechanism level, and a variable working condition milling force prediction model based on machine tool power consumption is established, thereby realizing accurate prediction of tool wear and cutting force under any working condition. The method provided by the present invention overcomes the shortcomings of other indirect monitoring signals in terms of versatility and extensibility. At the same time, the present invention is relatively simple to install and maintain, and has higher feasibility in actual production line deployment.

The invention discloses a meteorological data analysis method, device and equipment based on a large model agent and a medium, relates to the field of meteorological data intelligent management, is applied to a preset meteorological data analysis system, and comprises the following steps: when a main agent receives a to-be-processed meteorological message, determining and calling a target agent from a plurality of extreme weather scene agents; the main agent and the plurality of extreme weather scene agents are agents constructed by using a target large language model in advance; the target agent matches a first cue word template of the target agent based on a received main agent instruction so as to determine and call a target meteorological data acquisition tool; the target meteorological data acquisition tool matches a second cue word template of the target meteorological data acquisition tool based on a received target agent instruction so as to acquire meteorological data based on the determined target interface parameters; and the target agent determines a target answer based on the data acquisition result, so that the main agent replies a message in a dialogue form. And the limitation of the existing meteorological data application can be overcome.

The invention discloses a data communication method, a data communication device, data communication equipment and a medium, relates to the technical field of computers, and is applied to a complex programmable logic device which communicates with a south bridge chip in a preset type server and an external target substrate management controller chip through a simplified pin bus. Comprising the steps that target data sent by a south bridge chip is transmitted to a target substrate management controller chip, and after a TAR signal is monitored, a first synchronous communication signal fed back by the target substrate management controller chip is acquired; converting the first synchronous communication signal into a second synchronous communication signal; and transmitting the second synchronous communication signal to a south bridge chip, so that the south bridge chip communicates with the target substrate management controller chip based on the simplified pin bus after executing the preset short-time waiting operation. According to the application, the communication between the preset type server and the target substrate management controller chip based on the simplified pin bus is realized by connecting the complex programmable logic device in series.

The invention relates to application of an antioxidant liposome in preparation of a medicine for preventing and / or treating inner ear injury caused by active oxygen accumulation, and belongs to the field of medical technologies and biological medical materials. The antioxidant lipidosome is rutin-entrapped lipidosome, and the inner ear injury is preferably cis-platinum induced inner ear injury. The antioxidant liposome disclosed by the invention is used for inhibiting active oxygen accumulation, mitochondrial injury and cell apoptosis in cells; the compound is used for inhibiting auditory hair cell mitochondrial injury in cochlea. The antioxidant liposome disclosed by the invention can be used for effectively packaging medicines and improving the bioavailability and the stability of the medicines; the limitation of a tympanic membrane barrier and other biological barriers can be overcome, so that the medicine can effectively reach the inner ear part; precise targeted delivery of the medicine can be achieved, and it is ensured that the medicine is intensively released at the needed position.

The utility model provides a display module and terminal equipment, the display module comprises a display panel and a driver, the display panel comprises a display part, a bending part and a turnover part, the bending part is connected between the display part and the turnover part, the turnover part is located on one side of the display part in the thickness direction and is arranged opposite to the display part, and the driver is arranged on the turnover part. The folding part comprises a first part and a second part, the first part is connected between the bending part and the second part, the first part comprises a first surface in the thickness direction, the first surface deviates from the display part, the second part comprises a second surface in the thickness direction, the second surface deviates from the display part, and the driver is installed on the second surface of the second part; the second surface is located on the side, facing the display part, of the first surface. The display module is locally thinned, and the thickness bottleneck problem of the display module is solved.

The invention discloses an optical element surface defect data set manufacturing method based on deep learning. The method comprises the following steps: acquiring an optical element surface defect image; inputting the obtained defect image into a pre-trained defect detection model to carry out defect automatic detection; based on the defect detection result, drawing the outer contour of each defect by using a contour retrieval method, counting the corresponding defect type and defect total number, and then generating a contour retrieval result; carrying out rapid manual correction on the obtained contour retrieval result; and generating a label of the optical element surface defect image. The defect detection model is a semantic segmentation network, can not only judge whether defects exist or not and perform defect classification, but also can realize defect positioning and extraction at a pixel level. According to the method, the probability of false detection and missing detection under a complex background when the defect pixel-level label is manufactured is reduced, and the manufacturing efficiency and the manufacturing precision of the surface defect data set of the optical element are greatly improved.

The invention belongs to the field of TBM shield tail gap measurement, and particularly relates to a method for non-contact measurement of a gap between an open TBM shield tail and a surrounding rock, and the method combines Blender software to establish a virtual scene comprising the surrounding rock, a TBM shield, a reflective sticker, a binocular camera and an LED spotlight. The textures of the TBM shield, the surrounding rock and the reflective sticker in the virtual scene can be set according to a real image, a large number of binocular camera images can be rendered through changes of the textures and the surrounding rock surface, meanwhile, a gap between the tail of the TBM shield and the surrounding rock under a corresponding binocular graph is obtained through a written blender script, and a data set is generated. The data set is used for building a neural network model on a server, training is carried out, and a training weight is obtained; and then deploying the model and the weight into a measuring device, namely shooting an image of the binocular camera through the measuring device, and measuring the gap between the tail part of the shield and the surrounding rock.

The invention provides a quantum bit gate fidelity calibration method and device, electronic equipment and a medium. The quantum bit gate fidelity calibration method comprises the following steps: determining a first quantum bit gate in a plurality of quantum bit gates of a target quantum bit; obtaining a first fidelity of the first quantum bit gate; determining a second quantum bit gate to be calibrated and a first calibration means for calibrating the second quantum bit gate according to the first fidelity; and calibrating the second quantum bit gate based on the first calibration means. According to the embodiment of the invention, the calibration efficiency of the fidelity of the quantum bit gate can be improved. The embodiment of the invention can be applied to various scenes such as quantum computing and quantum communication.

The invention discloses a synthetic aperture radar image target detection method and device, equipment and a storage medium. The method comprises the following steps: acquiring a to-be-detected SAR image; performing denoising processing on the SAR image by using a denoising network; establishing an integrated target detection model which comprises a denoising network and a subsequent open vocabulary target detection model, and training the integrated model by using an improved bounding box regression loss function constructed based on angular point distance and side edge overlapping information; and inputting the denoised SAR image and text prompt into the trained open vocabulary target detection model for feature extraction and target detection, and outputting a detection result. According to the method, the denoising technology and open vocabulary target detection are combined, the problem that speckle noise is not fully processed in the current SAR target detection field is solved, meanwhile, the limitation of traditional target detection on fixed categories is overcome, the target detection precision is improved, and the applicability and robustness of the model are improved.

The invention discloses a GNSS (Global Navigation Satellite System) and wind cloud satellite assisted meteorological and hydrological coupled runoff forecasting method. The method comprises the following steps: 1, GNSS two-dimensional water vapor inversion; 2, performing water vapor inversion on the Fengyun No.4; 3, performing three-dimensional variation assimilation on the precipitable water volume inverted by the GNSS and the precipitable water volume inverted by the FY-4 star A based on a WRF meteorological mode; and 4, runoff forecasting is carried out based on the WRF-Hydro hydrological model. The method is simple in step and reasonable in design, three-dimensional variational assimilation is performed on the precipitable water volume inversed by the GNSS and the precipitable water volume inversed by the FY-4 star A based on the WRF meteorological mode, accurate meteorological driving data is provided for a WRF-Hydro hydrological model, the dependence of WRF meteorological mode data assimilation on conventional meteorological observation data in traditional meteorological and hydrological coupling forecast is avoided, and the method is suitable for popularization and application. And the applicability of the WRF and WRF-Hydro model coupling mode in the meso-and small-scale watershed in the conventional data scarcity region is further improved.

The invention discloses an energy efficiency optimization system for training and optimizing according to actual data, and relates to the technical field of energy efficiency optimization. Comprising an energy consumption prediction model, a temperature optimization module, an adaptive control module, a data collection module, a model training module, a variable optimization module, a prediction maintenance module, a collaborative optimization module, a user operation module and an algorithm updating module. According to the energy efficiency optimization system for training and optimizing according to the actual data, the prediction model of the system is trained and optimized by using the actual data, and when the actual energy use condition changes, adjustment can be made in time to achieve the purpose of dynamic adjustment, so that the limitation of a fixed model and an algorithm is avoided, and the applicability of the system is improved; the method is particularly suitable for kitchen application scenes, and meanwhile, more input variables are continuously introduced in combination with actual situations to further improve the accuracy and reliability of the prediction model, so that the implementation effect of energy-saving measures is improved.

The invention discloses a specific cell population analysis and screening method based on RCA-FISH and application of the specific cell population analysis and screening method. A target sequence region which is high in hybridization efficiency, high in specificity and free of an RNA advanced structure is screened out from an RNA sequence of a cell or tissue to be detected to design a primary hybridization probe, and the primary hybridization probe is composed of a lock-type probe and an RCA initiation probe; the method comprises the following steps: pre-treating a primary probe, hybridizing, carrying out a probe cyclization connection reaction, amplifying a signal by rolling circle amplification, and labeling cells by a fluorescent probe, so as to be used for flow cytometry analysis / sorting. The invention has the characteristics of simple probe preparation, high detection efficiency, strong specificity, strong signal amplification and the like.

The invention discloses a matching method and system based on a 5G network, Beidou positioning and non-line-of-sight microwave, and relates to the technical field of target signal positioning, and the matching method comprises the steps: building a static and dynamic combined calibration data set through obtaining high-precision geographic position information and real-time signal intensity data, and carrying out the calibration of the calibration data set; and adaptive direction adjustment and rapid focusing of the antenna are supported, and efficient communication and accurate positioning in a complex scene are realized. The calibration matching model is trained based on the calibration data set, so that the precision and adaptability of the model under multiple geographical environments and non-line-of-sight conditions are improved, an efficient antenna positioning mechanism is provided, and the stability and real-time performance of a communication link are guaranteed; the method is particularly suitable for complex environments such as disaster rescue, accident personnel can be quickly and accurately positioned, and rescue efficiency and action reliability are remarkably improved.

The invention relates to the technical field of computer vision and deep learning, in particular to a multi-source information small target ship identification and anomaly study and judgment method and device, and aims to improve the ship detection performance under a high-resolution remote sensing image by introducing a small target detection algorithm model based on an optical remote sensing image. The invention provides an improved YOLOv8x-CA-CFAR model and further provides a novel unsupervised domain adaptive classification model Multi-CDT in order to solve the problems that small target ship pixels in an optical remote sensing image are few and the features are not obvious, so that the transfer learning ability of different source data is enhanced, and the classification performance under the condition of lacking annotated data is improved. Finally, by constructing a complete multi-source information fusion framework, more accurate small target ship detection and classification are realized, the situation of matching failure of the optical remote sensing image and the AIS data can be effectively handled, and support for anomaly study and judgment is provided.

The invention discloses an ultra-high-temperature monofilament mechanical loading platform, a vacuum test device and a test method, and relates to the technical field of detection devices, in particular to an ultra-high-temperature monofilament mechanical loading platform comprising a tension loading module comprising two groups of moving cross beams moving oppositely or oppositely, a driving module for driving the moving cross beams to move, and a monofilament clamp, the movable cross beam is connected with the monofilament clamp through a sensor assembly; according to the ultrahigh-temperature monofilament mechanical loading platform, the vacuum test device and the test method, heat radiation generated by heating of the heating body is adopted to heat the workpiece, the problem of limitation on the material quality of the workpiece and the problem of uneven heating in the workpiece test process are solved, the heat preservation module is additionally arranged, the test temperature can be continuously increased, and the test efficiency is improved. According to the clamping tool, the ultrahigh-temperature environment of 2000 DEG C in a narrow space can be achieved, meanwhile, the groove body horizontally arranged in the heating body is adopted for bearing a workpiece, the influence of the clamping tool on workpiece drawing force measurement is reduced, the testing precision is guaranteed, and then the effectiveness of a testing result is promoted to be improved.

The invention relates to a general control or regulation system, and discloses an inertial measurement unit modeling simulation method and system based on digital twinning. The method comprises the following steps: dividing an inertial measurement unit into six basic components, and constructing a digital twin model corresponding to each basic component in modeling software; importing the digital twin models corresponding to the basic components into a simulation platform library through modeling software; when the inertial measurement unit based on digital twinning performs modeling simulation work, initial parameters required by simulation analysis are provided through an input source, and a gyroscope and an accelerometer perform mathematical solution on the sensed parameters and the initial parameters respectively and then output corresponding gyroscope square wave signals and current signals; the current signal is converted into a voltage signal through the I / F conversion circuit, and the inner DSP circuit converts the collected gyroscope square wave signal and the voltage signal into a gyroscope pulse and an accelerometer pulse respectively and then sends the gyroscope pulse and the accelerometer pulse to the outer DSP circuit so as to convert and output a simulation result required by a user.

This application relates to an integrated MEMS two-dimensional scanning detection system, a capacitance angle measurement method, and an apparatus. The integrated MEMS two-dimensional scanning detection system includes: a laser detection component and a magnetic circuit component disposed below the laser detection component. The laser detection component is an integral structure formed by connecting a scanning lens to a riveting area via a Y-shaped two-dimensional rotation axis. The magnetic circuit component is a hollow structure enclosed by two types of magnetic circuit modules, which are used to generate magnetic fields in different directional dimensions. The riveting area of ​​the laser detection component is connected to the magnetic circuit modules in the magnetic circuit component. The scanning lens is located in the cavity enclosed by multiple magnetic circuit modules, and under the drive of magnetic fields in different directional dimensions, the Y-shaped two-dimensional rotation axis drives the scanning lens to rotate in the corresponding directional dimension within the cavity. This integrated MEMS two-dimensional scanning detection system can reduce the overall size of the electromagnetic scanning mirror.

The utility model discloses a kind of carbon black granule screening machines, including frame and screening mechanism, frame: its inside front and back both sides are provided with mounting bracket, screening mechanism: it includes sieve tray, screen, adjusting assembly and connecting assembly, the sieve tray is rotationally connected in the inside of mounting bracket, four sieve trays are staggered distribution up and down, the side of sieve tray far from the middle of frame is discharge end, screen is all set in the inside of sieve tray, adjusting assembly is used for the angle adjustment of sieve tray, connecting assembly is used for the connection of frame and mounting bracket, the carbon black granule screening machine, with multiple-stage screening device, by setting screen of different aperture to carry out multiple-stage screening work, the discharge end of screen is located equipment's front and back both sides respectively, avoid the restriction of space, it is convenient to erect external conveying device, angle adjusting device is also provided, the inclination of different screen can be automatically adjusted, can guarantee screening quality without changing amplitude.

This utility model discloses a sound-generating unit, including a diaphragm assembly, a frame, a voice coil, and a centering support. The frame includes a housing connecting the diaphragm assembly, and the housing has a connecting arm extending away from the diaphragm assembly. The bottom end of the connecting arm has an outwardly extending extension arm. The connecting arm connects to the inner peripheral wall of the voice coil, and the bottom surface of the voice coil connects to the extension arm. The centering support includes an inner mounting part, a deformation part, and an outer mounting part connected sequentially from the inside to the outside. The bottom surface of the inner mounting part connects to the extension arm. This sound-generating unit effectively improves the connection stability between the voice coil and the frame, reducing the risk of the voice coil falling off. Simultaneously, the inner mounting part of the centering support is directly bonded to the bottom surface of the extension arm, rather than the outer wall or bottom surface of the voice coil in traditional structures. This avoids the limitation of the bonding area caused by the thickness of the voice coil itself, further enhancing the connection reliability between the centering support and the vibration system. Thus, while increasing the amplitude, it significantly improves the structural stability of the large-amplitude sound-generating unit.

This invention discloses a data-driven method for monitoring marine phytoplankton abundance using underwater acoustic networks. The method includes: constructing and training a multi-level spatiotemporal feature ensemble model based on historical marine phytoplankton abundance and corresponding marine environmental data to determine the optimal spatial location and monitoring time window of the underwater acoustic network nodes; constructing a teacher model for channel prediction, including a multi-layer cascaded structure and residual modules, and compressing the teacher model into a student model using spatiotemporal knowledge distillation; training the student model to achieve real-time channel state prediction at the underwater acoustic network nodes; matching suitable underwater acoustic communication devices and seasonal optimal routing strategies to each underwater acoustic network node based on the optimal spatial location and real-time predicted channel state, and performing adaptive modulation and coding at the link level, while simultaneously monitoring phytoplankton abundance using the underwater acoustic network. This invention can improve data throughput and prediction accuracy under strict energy consumption constraints.

The invention discloses a shale total organic carbon content intelligent prediction method based on experience constraint, and relates to the technical field of geophysical logging. After a sample data set comprising a training set and a test set is constructed according to logging information of a research area, a wave impedance curve is reconstructed, multiple pieces of TOC sample data are obtained, a total organic carbon content empirical model is determined based on a DEN-GR correction LogR model and introduced into a fitness function of a GWO algorithm, an SVR model is optimized by utilizing the GWO algorithm and the TOC sample data in the training set, and the total organic carbon content is obtained. And determining an optimal solution of a penalty coefficient and a kernel function parameter in the SVR model, obtaining the trained SVR model, verifying the accuracy of the SVR model for predicting the total organic carbon content of the shale by adopting TOC sample data in the test set, and applying the verified SVR model to intelligent prediction of the total organic carbon content of the shale. According to the method, empirical constraint and the GWO-SVR algorithm are combined, accurate prediction of the total organic carbon content of shale is achieved, and a basis is provided for guiding exploration and development of shale reservoirs.

The application provides a UAV blind path inspection system based on photoelectric image acquisition and AI intelligent analysis, comprising a UAV edge computing node, a ground relay gateway and a mobile management end. A microcontroller in the UAV edge computing node reads photoelectric images for in-chip edge inference, discards original image pixel data after extracting a structured feature vector containing obstacle category information, and broadcasts and sends the structured feature vector through an onboard low-power wide-area network transparent transmission module. The upper computer of the ground relay gateway reconstructs the received structured feature vector into an Internet of Things message and pushes it to a cloud server. The mobile management end obtains the message and instantiates the structured feature vector as a warning anchor point in an electronic map, and simultaneously sends a status synchronization update message to the cloud server in response to a verification instruction to erase the warning anchor point. The system realizes dimension reduction at the data source, reduces the communication bandwidth demand of long-distance transmission, and forms a data closed loop for hidden danger investigation.

This invention relates to the field of water remediation technology, specifically to a piezoelectric catalytic component and a groundwater remediation system. The piezoelectric catalytic component includes: an upper part of a piezoelectric catalytic body with a spiral channel communicating with an inlet, and a lower part with a cavity; the cross-sectional diameter of the spiral channel gradually decreases from the inlet to the end; a column is provided in the cavity, and a piezoelectric film is spirally wound around the column; the end of the spiral channel is close to the piezoelectric film at the upper end of the column; the piezoelectric film receives water containing organic pollutants flowing in from the spiral channel and catalytically degrades the organic pollutants through piezoelectric conversion; this application combines the static pressure of the water flow, accelerates the water flow through the spiral channel, the flow velocity gradually increases from top to bottom, the hydraulic impact load is correspondingly enhanced, the mechanical force flowing through the piezoelectric film is increased, low-frequency vibration excites the piezoelectric catalytic effect, maximizes the catalytic degradation capacity of the piezoelectric material, and thus improves the catalytic degradation efficiency of the piezoelectric material.